jLSTM_protein

This is the recommended new JAVA-package of "Long Short-Term Memory" for Protein classification (jLSTM_protein).
The implementation of the LSTM neural network is the same as in the C package and performs and behaves identically but faster.
jLSTM_protein is multithreaded and therefore uses effectively multicore and -processor machines. Using more than one
thread results in faster computation as in the C package. Each thread individually computes the gradients with a local weight matrix and updates a global weight matrix performing asynchronous stochastic gradient. jLSTM_protein uses Biojava 1.6
for reading FASTA sequences. The Biojava package is included and needs no separate installation.

For Remote Homology detection experiments adding
positive training sequences with PSI-BLAST searches gives best results.
To do this we offer a complete environment based on Perl and NCBI PSI-BLAST.
Here is the README.

(j)LSTM as Logistic Regression with the Spectrum Kernel (new)

LSTM logistic regression / spectrum kernel is a stripped down LSTM which can be interpreted
as logistic regression with the spectrum kernel for sequence classification.
For any step in the DNA sequence and a given k a k-mer string vector is
build and fed into the network. The LSTM architecture is just two memory
cells and no input- or output gates. The memory cells are not connected
with each other. The squashing function h is the identity function.
LSTM in this version weighs important k-mers for the classification and therefore can
be used as an additional pattern recognizer based on k-mers.

Download, compile and tryout the software implementation with examples
in tar.gz format LSTM.tar.gz

For Remote Homology detection experiments adding
positive training sequences with PSI-BLAST searches gives best results.
To do this we offer a complete environment based on Perl and NCBI PSI-BLAST.
Here is the README.

LICENSE, WARRANTY, AND LIABILITY
This programm is freely available under the GNU General Public License (GPL).
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.